This repository contains a data engineering project that examines the predictability of the collapse of Silicon Valley Bank (SVB) and First Republic Bank through a data-driven approach. The project includes an analysis of the data from these banks to build a predictive model that assesses the risk of their failure, as well as a detailed analysis of the reasons behind the collapse of SVB and First Rebulic Bank.
The goal of this project is to investigte whether the failures of SVB and First Republic Bank were predicatable or not, and to provide valuable insights into the predictability of bank failures and highlight some important proactive measures to prevent them.
The repository includes the necessary code, datasets, and documentation required to replicate the project's findings and build upon its methodology. The project is divided into the following sections:
-
Data Collection: Collection of data on SVB and First Republic Bank, including financial statements, balance sheets, and other relevant data.
-
Data Cleaning and Preprocessing: Cleaning and preprocessing the collected data to ensure its accuracy and consistency.
-
Data Analysis and Modeling: Analyzing the cleaned data and building a predictive model to assess the risk of failure of SVB and First Republic Bank
-
Failure Analysis: A detailed analysis of the reasons behind the collapse of SVB and First Republic Bank